Learn how granular attribute-based access control (ABAC) prevents context window injections in AI infrastructure using quantum-resistant security and MCP.

Explore how AI-driven anomaly detection enhances the security of Model Context Protocol (MCP) deployments, protecting AI infrastructure from evolving threats with real-time insights.

Security researchers uncovered a range of cyber issues targeting AI systems that users and developers should be aware of — ...

MCP, or Model Context Protocol, was proposed by Anthropic and is quickly becoming the industry’s standard interface between AI systems and traditional platforms. In a nutshell, it wants to be the AI ...

An MCP Server uses the Model Context Protocol (MCP) to link AI models with tools and data sources. These lightweight programs securely handle tasks like accessing files, databases, or APIs, enabling ...

The Model Context Protocol (mCP) is reshaping how artificial intelligence (AI) systems interact with data, tools, and environments. Developed as an open source standard by Anthropic, mCP simplifies ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Vivek Yadav, an engineering manager from ...

Model Context Protocol makes it far easier to integrate LLMs and your APIs. Let’s walk through how MCP clients and servers communicate, securely. Every new protocol introduces its own complexities.

An MCP Server is a simple program that lets AI models securely access data and tools using the Model Context Protocol (MCP). FastMCP is a Python framework that helps you build MCP servers and clients.